org.nd4j.linalg.factory.Nd4j.concat()方法的使用及代码示例

x33g5p2x  于2022-01-24 转载在 其他  
字(8.6k)|赞(0)|评价(0)|浏览(171)

本文整理了Java中org.nd4j.linalg.factory.Nd4j.concat()方法的一些代码示例，展示了Nd4j.concat()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Nd4j.concat()方法的具体详情如下：
包路径：org.nd4j.linalg.factory.Nd4j
类名称：Nd4j
方法名：concat

Nd4j.concat介绍

[英]Concatneate ndarrays along a dimension
[中]沿着一个维度连续排列

代码示例

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Concatenates two matrices horizontally.
 * Matrices must have identical
 * numbers of rows.
 *
 * @param arrs
 */
public INDArray hstack(INDArray... arrs) {
  return Nd4j.concat(1, arrs);
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Concatenates two matrices vertically. Matrices must have identical
 * numbers of columns.
 *
 * @param arrs
 */
@Override
public INDArray vstack(final INDArray... arrs) {
  return Nd4j.concat(0, arrs);
}

代码示例来源：origin: deeplearning4j/dl4j-examples

static INDArray append(INDArray arr1, INDArray values, int dimension) {
  if(dimension == -1) {
    return Nd4j.toFlattened(arr1, values);
  } else {
    return Nd4j.concat(dimension, arr1, values);
  }
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Get a view of the underlying array
 * relative to the size of the actual array.
 * (Sometimes there are overflows in the internals
 * but you want to use the internal INDArray for computing something
 * directly, this gives you the relevant subset that reflects the content of the list)
 * @return the view of the underlying ndarray relative to the collection's real size
 */
public INDArray array() {
  List<INDArray> retList = new ArrayList<>(list.size());
  for(X x : list) {
    retList.add(x.array());
  }
  return Nd4j.concat(0,retList.toArray(new INDArray[retList.size()]));
}

代码示例来源：origin: deeplearning4j/dl4j-examples

System.out.println(ones);
INDArray combined = Nd4j.concat(0,zeros,ones);
INDArray combined2 = Nd4j.concat(1,zeros,ones);

代码示例来源：origin: deeplearning4j/nd4j

return Nd4j.concat(0,resultList.toArray(new INDArray[resultList.size()]));

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Append the given
 * array with the specified value size
 * along a particular axis
 * @param arr the array to append to
 * @param padAmount the pad amount of the array to be returned
 * @param val the value to append
 * @param axis the axis to append to
 * @return the newly created array
 */
public static INDArray append(INDArray arr, int padAmount, double val, int axis) {
  if (padAmount == 0)
    return arr;
  long[] paShape = ArrayUtil.copy(arr.shape());
  if (axis < 0)
    axis = axis + arr.shape().length;
  paShape[axis] = padAmount;
  INDArray concatArray = Nd4j.valueArrayOf(paShape, val);
  return Nd4j.concat(axis, arr, concatArray);
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Append the given
 * array with the specified value size
 * along a particular axis
 * @param arr the array to append to
 * @param padAmount the pad amount of the array to be returned
 * @param val the value to append
 * @param axis the axis to append to
 * @return the newly created array
 */
public static INDArray prepend(INDArray arr, int padAmount, double val, int axis) {
  if (padAmount == 0)
    return arr;
  long[] paShape = ArrayUtil.copy(arr.shape());
  if (axis < 0)
    axis = axis + arr.shape().length;
  paShape[axis] = padAmount;
  INDArray concatArr = Nd4j.valueArrayOf(paShape, val);
  return Nd4j.concat(axis, concatArr, arr);
}

代码示例来源：origin: deeplearning4j/nd4j

return Nd4j.concat(0,arrList.toArray(new INDArray[arrList.size()]));

代码示例来源：origin: deeplearning4j/nd4j

return Nd4j.concat(0,arrList.toArray(new INDArray[arrList.size()]));

代码示例来源：origin: deeplearning4j/dl4j-examples

static INDArray insert(INDArray arr1, int index, INDArray values, int dimension) {
  if(dimension == -1) {
    INDArray flat1 = Nd4j.toFlattened(arr1);
    INDArray flatValues = Nd4j.toFlattened(values);
    INDArray firstSlice = flat1.get(NDArrayIndex.interval(0, index));
    INDArray secondSlice = flat1.get(NDArrayIndex.interval(index, flat1.length()));
    return Nd4j.toFlattened(firstSlice, flatValues, secondSlice);
  } else {
    INDArray firstSlice = arr1.get(createIntervalOnDimension(dimension, false,
      0, index));
    INDArray secondSlice = arr1.get(createIntervalOnDimension(dimension, false,
      index, arr1.shape()[dimension]));
    return Nd4j.concat(dimension, firstSlice, values, secondSlice);
  }
}

代码示例来源：origin: deeplearning4j/dl4j-examples

static INDArray delete(int dimension, INDArray arr1, int... interval) {
  int length = interval.length;
  int lastIntervalValue = interval[length - 1];
  if(dimension == -1) {
    INDArray array1 = arr1.get(NDArrayIndex.interval(0, interval[0]));
    if(lastIntervalValue == arr1.length() - 1) {
      return Nd4j.toFlattened(array1);
    } else {
      INDArray array2 = arr1.get(NDArrayIndex.interval(lastIntervalValue + 1,
        arr1.length()));
      return Nd4j.toFlattened(array1, array2);
    }
  } else {
    INDArray array1 = arr1.get(createIntervalOnDimension(dimension, false, 0, interval[0]));
    if(lastIntervalValue == arr1.shape()[dimension] - 1) {
      return array1;
    } else {
      INDArray array2 = arr1.get(createIntervalOnDimension(dimension, false,
        lastIntervalValue + 1,
        arr1.shape()[dimension]));
      return Nd4j.concat(dimension, array1, array2);
    }
  }
}

代码示例来源：origin: deeplearning4j/dl4j-examples

INDArray concatenatedAxisZero = Nd4j.concat(0, Nd4j.create(3, 2), Nd4j.create(5, 2));
print("Concatenated arrays on dimension zero", concatenatedAxisZero);
INDArray concatenatedAxisOne = Nd4j.concat(1, Nd4j.create(3, 2), Nd4j.create(3, 5));
print("Concatenated arrays on dimension 1", concatenatedAxisOne);

代码示例来源：origin: org.nd4j/nd4j-api

/**
 * Concatenates two matrices horizontally.
 * Matrices must have identical
 * numbers of rows.
 *
 * @param arrs
 */
public INDArray hstack(INDArray... arrs) {
  return Nd4j.concat(1, arrs);
}

代码示例来源：origin: org.nd4j/nd4j-api

/**
 * Concatenates two matrices vertically. Matrices must have identical
 * numbers of columns.
 *
 * @param arrs
 */
@Override
public INDArray vstack(final INDArray... arrs) {
  return Nd4j.concat(0, arrs);
}

代码示例来源：origin: neo4j-graph-analytics/ml-models

private void diffuse(List<Pruning.Feature> featuresList) {
  INDArray ndDiffused = Nd4j.create(embedding.shape());
  Nd4j.copy(embedding, ndDiffused);
  featuresList.addAll(featuresList);
  features = featuresList.toArray(new Pruning.Feature[0]);
  for (int i = features.length / 2; i < features.length; i++) {
    features[i] = new Pruning.Feature("diffuse", features[i]);
  }
  for (int diffIteration = 0; diffIteration < diffusionIterations; diffIteration++) {
    INDArray ndDiffusedTemp = Nd4j.create(embedding.shape());
    nodeQueue.set(0);
    final ArrayList<Future<?>> futures = new ArrayList<>();
    for (int i = 0; i < concurrency; i++) {
      futures.add(executorService.submit(new DiffusionTask(ndDiffused, ndDiffusedTemp)));
    }
    ParallelUtil.awaitTermination(futures);
    ndDiffused = ndDiffusedTemp;
  }
  embedding = Nd4j.concat(1, embedding, ndDiffused);
}

代码示例来源：origin: org.nd4j/nd4j-api

/**
 * Append the given
 * array with the specified value size
 * along a particular axis
 * @param arr the array to append to
 * @param padAmount the pad amount of the array to be returned
 * @param val the value to append
 * @param axis the axis to append to
 * @return the newly created array
 */
public static INDArray append(INDArray arr, int padAmount, double val, int axis) {
  if (padAmount == 0)
    return arr;
  int[] paShape = ArrayUtil.copy(arr.shape());
  if (axis < 0)
    axis = axis + arr.shape().length;
  paShape[axis] = padAmount;
  INDArray concatArray = Nd4j.valueArrayOf(paShape, val);
  return Nd4j.concat(axis, arr, concatArray);
}

代码示例来源：origin: org.nd4j/nd4j-api

/**
 * Append the given
 * array with the specified value size
 * along a particular axis
 * @param arr the array to append to
 * @param padAmount the pad amount of the array to be returned
 * @param val the value to append
 * @param axis the axis to append to
 * @return the newly created array
 */
public static INDArray prepend(INDArray arr, int padAmount, double val, int axis) {
  if (padAmount == 0)
    return arr;
  int[] paShape = ArrayUtil.copy(arr.shape());
  if (axis < 0)
    axis = axis + arr.shape().length;
  paShape[axis] = padAmount;
  INDArray concatArr = Nd4j.valueArrayOf(paShape, val);
  return Nd4j.concat(axis, concatArr, arr);
}

代码示例来源：origin: improbable-research/keanu

/**
 * @param dimension the dimension along which the tensors will be joined
 * @param toConcat  an array of IntegerTensor
 * @return  an IntegerTensor with toConcat joined along existing dimension
 * <p>
 * e.g. A, B, C = IntegerTensor.ones(4, 2)
 * <p>
 * IntegerTensor.concat(0, A, B, C) gives IntegerTensor.ones(12, 2)
 */
static IntegerTensor concat(int dimension, IntegerTensor... toConcat) {
  INDArray[] concatAsINDArray = new INDArray[toConcat.length];
  for (int i = 0; i < toConcat.length; i++) {
    concatAsINDArray[i] = Nd4jIntegerTensor.unsafeGetNd4J(toConcat[i]).dup();
    if (concatAsINDArray[i].shape().length == 0) {
      concatAsINDArray[i] = concatAsINDArray[i].reshape(1);
    }
  }
  INDArray concat = Nd4j.concat(dimension, concatAsINDArray);
  return new Nd4jIntegerTensor(concat);
}

代码示例来源：origin: improbable-research/keanu

/**
 * @param dimension the dimension along which the tensors will be joined
 * @param toConcat  an array of DoubleTensor
 * @return  a DoubleTensor with toConcat joined along an existing dimension
 * <p>
 * e.g. A, B, C = DoubleTensor.ones(4, 2)
 * <p>
 * DoubleTensor.concat(0, A, B, C) gives DoubleTensor.ones(12, 2)
 */
static DoubleTensor concat(int dimension, DoubleTensor... toConcat) {
  INDArray[] concatAsINDArray = new INDArray[toConcat.length];
  for (int i = 0; i < toConcat.length; i++) {
    concatAsINDArray[i] = Nd4jDoubleTensor.unsafeGetNd4J(toConcat[i]).dup();
    if (concatAsINDArray[i].shape().length == 0) {
      concatAsINDArray[i] = concatAsINDArray[i].reshape(1);
    }
  }
  INDArray concat = Nd4j.concat(dimension, concatAsINDArray);
  return new Nd4jDoubleTensor(concat);
}

内容来源于网络，如有侵权，请联系作者删除！

Nd4j

相关文章

    查看更多

    热门标签

    更多
    JavaquerypythonNode开发语言requestUtil数据库Table后端算法LoggerMessageElementParser

    最新文章

    更多

    Nd4j类方法

    • 蜀ICP备13028337号-1 大数据知识库 https://www.saoniuhuo.com © All rights reserved
    • 本站内容来源互联网,如果侵犯您的权益请联系我们删除, 联系方式：448109455@qq.com